Rotavirus is the most common cause of acute gastroenteritis in infants and children worldwide. The functional correlation of B-and T-cells to long-lasting immunity against rotavirus infection in the literature is limited. In this work, a series of computational immuno-informatics approaches were applied and identified 28 linear B-cells, 26 conformational B-cell, 44 T C cell and 40 T H cell binding epitopes for structural and non-structural proteins of rotavirus. Further selection of putative B and T cell epitopes in the multi-epitope vaccine construct was carried out based on immunogenicity, conservancy, allergenicity and the helical content of predicted epitopes. An in-silico vaccine constructs was developed using an N-terminal adjuvant (RGD motif) followed by T C and T H cell epitopes and B-cell epitope with an appropriate linker. Multi-threading models of multi-epitope vaccine construct with Band T-cell epitopes were generated and molecular dynamics simulation was performed to determine the stability of designed vaccine. Codon optimized multi-epitope vaccine antigens was expressed and affinity purified using the E. coli expression system. Further the T cell epitope presentation assay using the recombinant multi-epitope constructs and the T cell epitope predicted and identified in this study have not been investigated. Multiepitope vaccine construct encompassing predicted B-and T-cell epitopes may help to generate long-term immune responses against rotavirus. The computational findings reported in this study may provide information in developing epitope-based vaccine and diagnostic assay for rotavirus-led diarrhea in children's.

All approved coronavirus disease 2019 (COVID-19) vaccines in current use are safe, effective, and reduce the risk of severe illness. Although data on the immunological presentation of patients with COVID-19 is limited, increasing experimental evidence supports the significant contribution of B and T cells towards the resolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Despite the availability of several COVID-19 vaccines with high efficacy, more effective vaccines are still needed to protect against the new variants of SARS-CoV-2. Employing a comprehensive immunoinformatic prediction algorithm and leveraging the genetic closeness with SARS-CoV, we have predicted potential immune epitopes in the structural proteins of SARS-CoV-2. The S and N proteins of SARS-CoV-2 and SARS-CoVs are main targets of antibody detection and have motivated us to design four multi-epitope vaccines which were based on our predicted B- and T-cell epitopes of SARS-CoV-2 structural proteins. The cardinal epitopes selected for the vaccine constructs are predicted to possess antigenic, non-allergenic, and cytokine-inducing properties. Additionally, some of the predicted epitopes have been experimentally validated in published papers. Furthermore, we used the C-ImmSim server to predict effective immune responses induced by the epitope-based vaccines. Taken together, the immune epitopes predicted in this study provide a platform for future experimental validations which may facilitate the development of effective vaccine candidates and epitope-based serological diagnostic assays.

In this paper, the chain flexibility of P4-VP was tried to increase by lowering its glass transition temperature (T g ) and by increasing its amorphous region by copolymerizing with butyl methacrylate. The copolymers were prepared in five different feed molar ratios to optimize the required properties such as higher room temperature conductivity and film-forming capacity. The conductivity and conduction behavior of the copolymers, as well as their hydrochloride and hydrobromide salts, have been reported. The copolymers were prepared by solution polymerization technique, using tetrahydrofuran as solvent at 60°C, and the salts were prepared by simple acidification. The copolymers and their salts were characterized by scanning electron micrographs, infrared, proton nuclear magnetic resonance, thermogravimetric, differential scanning calorimetry and AC impedance measurements. There was about 10 3 -to 10 4 -fold increase in room temperature conductivity of these plasticized polyelectrolytes. The conduction behavior was found to be predominantly ionic. The scientific importance of this paper is that, unlike polymer electrolytes, no external salt is used; instead the virgin polymer and polyelectrolytes are used for conductivity measurements.

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Background: Riemerella anatipestifer (R. anatipestifer) is a gram negative, microaerophilic, non-motile, bipolar bacteria. High genetic diversity and molecular differentiation were reported among field isolates. Although the bacterium causes one of the most economically important duck diseases in the north-eastern region of India, little work has been done on isolation, identification and molecular characterization of the bacteria. Hence, the present investigation was undertaken with a view to characterize the R. anatipestifer isolates from ducks of Assam.Methods: Phenotypic and molecular identification of R. anatipestifer isolates from domesticated ducks of Assam, India were carried out during the period from February, 2019 to January 2020. A total of 624 samples (Ocular swab, throat swab, liver, spleen, kidney, brain, heart, lung) from ducks comprising of apparently healthy, ailing and dead ducks were collected from five districts of Assam, India were processed to isolate and identify the bacteria. The tentative identification of the bacteria was done based on phenotypic characteristics viz., colony morphology, growth characteristics and biochemical reactions. All the phenotypically positive isolates were further subjected to molecular identification based on PCR assay targeting 16S rRNA gene and ERIC sequence.Result: The bacteria could be isolated from different field samples. The highest percentage of the samples that yielded the bacteria are from brain (76%) followed by spleen (74%) of dead ducks and less number of ocular swab (33%) from apparently healthy ducks were found positive. Sequencing of the amplified product of the selected R. anatipestifer isolates targeting 16S rRNA gene revealed homology percentage of 96.5-100%. Further, sequences representing five geographical locations were submitted to NCBI gene bank. Phylogenetic studies of the isolates indicated that there is prevalence of at least two genetically different strains of R. anatipestifer in the study area. The study suggested that the R. anatipestifer infection is endemic in Assam causing varying rate of morbidity (39%) and mortality (53%) and molecular based confirmation is necessary besides phenotypic identification.